The goal of the present research was to assess, under controlled laboratory conditions, the accuracy and precision of a prototype device (named 'P.ALP': Ph.D. Air-quality Low-cost Project) developed for PM(2.5) concentration level monitoring. Indeed, this study follows a complementary manuscript (previously published) focusing on the in-field evaluation of the device's performance. Four P.ALP prototypes were co-located with the reference instrument in a calm-air aerosol chamber at the NIOSH laboratories in Pittsburgh, PA (USA), used by the Center for Direct Reading and Sensor Technologies. The devices were tested for 10 monitoring days under several exposure conditions. To evaluate the performance of the prototypes, different approaches were employed. After the data from the devices were stored and prepared for analysis, to assess the accuracy (comparing the reference instrument with the prototypes) and the precision (comparing all the possible pairs of devices) of the P.ALPs, linear regression analysis was performed. Moreover, to find out the applicability field of this device, the US EPA's suggested criteria were adopted, and to assess error trends of the prototype in the process of data acquisition, Bland-Altman plots were built. The findings show that, by introducing ad hoc calibration factors, the P.ALP's performance needs to be further implemented, but the device can monitor the concentration trend variations with satisfying accuracy. Overall, the P.ALP can be involved in and adapted to a wide range of applications because of the inexpensive nature of the components, the small dimensions, and the high data storage capacity.

A worker’s personal exposure to respirable dust in occupational environments has traditionally been monitored using established methodologies which entail the collection of an 8-h representative sample that is sent away for laboratory analysis. While these methods are very accurate, they only provide information on the average exposure during a specific time period, generally a worker’s shift. The availability of relatively inexpensive aerosol sensors can allow researchers and practitioners to generate real-time data with unprecedented spatial and temporal granularity. Low-cost dust monitors (LCDM) were developed and marketed for air pollution monitoring and are mostly being used to help communities understand their local and even hyper-local air quality. Most of these integrated sensing packages cost less than $300 per unit, in contrast to wearable or area dust monitors specifically built for mining applications which have been around for decades but still average around $5000 each. At the National Institute for Occupational Safety and Health (NIOSH), we are leveraging the power of high-volume data collection from networks of LCDM to establish baseline respirable hazard levels and to monitor for changes on a seasonal basis as well as following any application of control technologies. We have seen the effective use and advantages of monitoring live data before, during, and after events like shift changes, operational changes, ventilation upgrades, adverse weather events, and machine maintenance. However, many factors have prevented a systematic adoption of LCDMs for exposure monitoring: concern for their analytical performance, the complexity of use, and lack of understanding of their value are some factors. This contribution outlines a 1-year case study at a mine in Wisconsin, USA, covering the installation, maintenance, data visualizations, and collaboration between NIOSH researchers and the industrial hygiene professionals at the mine. © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2024.

This study aimed to assess the performance, in terms of precision and accuracy, of a prototype (called "P.ALP"-Ph.D. Air Quality Low-cost Project) developed for monitoring PM(2.5) concentration levels. Four prototypes were co-located with reference instrumentation in four different microenvironments simulating real-world and working conditions, namely (i) office, (ii) home, (iii) outdoor, and (iv) occupational environments. The devices were evaluated for a total of 20 monitoring days (approximately 168 h) under a wide range of PM(2.5) concentrations. The performances of the prototypes (based on the light-scattering working principle) were tested through different statistical methods. After the data acquisition and data cleaning processes, a linear regression analysis was performed to assess the precision (by comparing all possible pairs of devices) and the accuracy (by comparing the prototypes against the reference instrumentation) of the P.ALP. Moreover, the United States Environmental Protection Agency (US EPA) criteria were applied to assess the possible usage of this instrumentation, and to evaluate the eventual error trends of the P.ALP in the data storage process, Bland-Altman plots were also adopted. The outcomes of this study underlined that the P.ALP performed differently depending on the microenvironment in which it was tested and, consequently, on the PM(2.5) concentrations. The device can monitor PM(2.5) variations with acceptable results, but the performance cannot be considered satisfactory at extremely low and remarkably high PM(2.5) concentrations. Thanks to modular components and open-source software, the tested device has the potential to be customized and adapted to better fit specific study design needs, but it must be implemented with ad hoc calibration factors depending on the application before being used in field.

The PDM3600 and PDM3700 are two closely related person-wearable dust monitors manufactured by Thermo Fisher Scientific. Both are based on tapered element oscillating microbalance technology and provide nearly real-time, mass-based readings of respirable dust concentrations. From a monitoring perspective, the primary difference between the models is the PDM3600 has an integrated cap lamp with attached inlet, while the PDM3700 has no cap lamp and a revised inlet attaches to the worker’s lapel. Using coals of varied origin and employing a wide range of concentrations, side-by-side measurements from these instruments were collected under controlled laboratory conditions and then compared. By use of ordinary least squares and weighted least squares regression methods, followed by mixed model analysis, results suggest there is no statistically significant or practical difference in instrument performance. The two monitors are equivalent for the field dust concentration measurements for which they were designed. © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2024.

Low-cost particulate matter (PM) sensors provide new methods for monitoring occupational exposure to hazardous substances, such as flour dust. These devices have many possible benefits, but much remains unknown about their performance for different exposure monitoring strategies in the workplace. We explored the performance of PM sensors for four different monitoring strategies (time-weighted average and high time resolution, each quantitative and semi-quantitative) for assessing occupational exposure using low-cost PM sensors in a field study in the industrial bakery sector. Measurements were collected using four types of sensor (PATS+, Isensit, Airbeam2, and Munisense) and two reference devices (respirable gravimetric samplers and an established time-resolved device) at two large-scale bakeries, spread over 11 participants and 6 measurement days. Average PM2.5 concentrations of the low-cost sensors were compared with gravimetric respirable concentrations for 8-h shift periods and 1-min PM2.5 concentrations of the low-cost sensors were compared with time-resolved PM2.5 data from the reference device (quantitative monitoring strategy). Low-cost sensors were also ranked in terms of exposure for 8-h shifts and for 15-min periods with a shift (semi-quantitative monitoring strategy). Environmental factors and methodological variables, which can affect sensor performance, were investigated. Semi-quantitative monitoring strategies only showed more accurate results compared with quantitative strategies when these were based on shift-average exposures. The main factors that influenced sensor performance were the type of placement (positioning the devices stationary versus personal) and the company or workstation where measurements were collected. Together, these findings provide an overview of common strengths and drawbacks of low-cost sensors and different ways these can be applied in the workplace. This can be used as a starting point for further investigations and the development of guidance documents and data analysis methods.

Research studying the intersection of occupational safety and health (OSH) and direct reading and sensor technologies (DRST) is sparse, with a specific lack of research available that has empirically considered ways that DRST may impact worker well-being. In this paper, the authors examine how organizations could utilize core elements of their health and safety management system (HSMS) to coordinate and execute DRST in the workplace to support worker well-being. National Institute for Occupational Safety and Health (NIOSH) researchers developed a 39-item questionnaire targeting OSH professionals to understand attitudes toward DRST and the current and intended uses of DRST at their place of employment. Eighty-eight OSH professionals completed the questionnaire between August and December 2021. Descriptive results of the study sample are provided but the focus of the study applies the open-ended responses to two questions, which was deductively analyzed. Descriptive results show that reliability and validity of data was a top concern while the open-ended qualitative feedback revealed three primary themes: (1) acceptability and trust in technology; (2) ease of use; and (3) support and guidelines. Results provide an opening to use core HSMS elements (i.e., management commitment and leadership, communication and coordination, and employee involvement) during DRST integration to demonstrate support for workers during times of ambiguity and change.

Direct-reading methodologies and real-time monitors will play a crucial role in workers' health and safety in the context of the Fourth Industrial Revolution. This article proposes that these technologies and other advancements will lead to a new stage of industrial hygiene, which may be called IH4.0. The Fourth Industrial Revolution is a way of describing the blurring of boundaries between the physical, digital, and biological worlds. There are several definitions for this revolution, but they all recognize the critical importance of data. Everyday life is already affected by data generated in different environments, some occupational and some not. The impact of data will become even more significant in the future, considering the characteristics of what is known as "Big Data." These characteristics are the high volume of data; the elevated velocity with which the data is generated; the variety of data of different natures; and the usefulness or value of collecting and modeling data. Even as IH4.0, industrial hygiene will continue to be organized according to the principles of anticipation, recognition, evaluation, and control (AREC). But like many other workplace activities, such as production, management, and quality control, industrial hygiene will be revolutionized by data. The profession has an opportunity and a responsibility to evolve because of a new understanding of data.

With the advent of new sensing technologies and robust field-deployable analyzers, monitoring approaches can now generate valuable hazard information directly in the workplace. This is the case for monitoring respirable dust and respirable crystalline silica concentration levels. Estimating the quartz amount of a respirable dust sample by nondestructive analysis can be carried out using portable Fourier transform infrared spectroscopy (FTIR) units. Real-time respirable dust monitors, combined with small video cameras, allow advanced assessments using the Helmet-CAM methodology. These two field-based monitoring approaches, developed by the National Institute for Occupational Safety and Health (NIOSH), have been trialed in a sandstone quarry. Twenty-six Helmet-CAM sessions were conducted, and forty-one dust samples were collected around the quarry and analyzed on site during two events. The generated data generated were used to characterize concentration levels for the monitored areas and workers, to identify good practices, and to illustrate activities that could be improved with additional engineered control technologies. Laboratory analysis on the collected samples complemented the field finding and provided an assessment of the performance of the field-based techniques. Only a fraction of the real-time respirable dust monitoring sessions data could be corrected with laboratory analysis. The average correction factor ratio was 5.0. Nevertheless, Helmet-CAM results provided valuable information for each session. The field-based quartz monitoring approach overestimated the concentration by a factor of 1.8, but it successfully assessed the quartz concentration trends in the quarry. The data collected could be used for the determination of a quarry calibration factor for future events. The quartz content in the dust was found to vary from 14% to 100%, and this indicates the need for multiple techniques in the characterization of respirable dust and quartz concentration and exposure. Overall, this study reports the importance of the adoption of field-based monitoring techniques when combined with a proper understanding and knowledge of the capabilities and limitations of each technique.

With advances in technology, there are an increasing number of direct-reading instruments available to occupational health and safety professionals to evaluate occupational aerosol exposures. Despite the wide array of direct-reading instruments available to professionals, adoption of direct-reading technology to monitor workplace exposures has been limited, partly due to a lack of knowledge on how the instruments operate, how to select an appropriate instrument, and challenges in data analysis techniques. This paper presents a review of direct-reading aerosol instruments available to occupational health and safety professionals, describes the principles of operation, provides guidance on instrument selection based on the workplace and exposure, and discusses data analysis techniques in an effort to overcome these barriers to adoption. This paper does not cover all direct-reading instruments for aerosols but only those that an occupational health and safety professional could use in a workplace to evaluate exposures. Therefore, this paper focuses on instruments that have the most potential for workplace use due to their robustness, past workplace use, and price with regards to return on investment. The instruments covered in this paper include those that measure aerosol number concentration, mass concentration and aerosol size distributions.

Over the last decade, technological advancements have been made available and applied in a wide range of applications in several work fields, ranging from personal to industrial enforcements. One of the emerging issues concerns occupational safety and health in the Fourth Industrial Revolution and, in more detail, it deals with how industrial hygienists could improve the risk-assessment process. A possible way to achieve these aims is the adoption of new exposure-monitoring tools. In this study, a systematic review of the up-to-date scientific literature has been performed to identify and discuss the most-used sensors that could be useful for occupational risk assessment, with the intent of highlighting their pros and cons. A total of 40 papers have been included in this manuscript. The results show that sensors able to investigate airborne pollutants (i.e., gaseous pollutants and particulate matter), environmental conditions, physical agents, and workers' postures could be usefully adopted in the risk-assessment process, since they could report significant data without significantly interfering with the job activities of the investigated subjects. To date, there are only few "next-generation" monitors and sensors (NGMSs) that could be effectively used on the workplace to preserve human health. Due to this fact, the development and the validation of new NGMSs will be crucial in the upcoming years, to adopt these technologies in occupational-risk assessment.

In the ever-expanding complexities of the modern-day mining workplace, the continual monitoring of a safe and healthy work environment is a growing challenge. One specific workplace exposure concern is the inhalation of dust containing respirable crystalline silica (RCS) which can lead to silicosis, a potentially fatal lung disease. This is a recognized and regulated health hazard, commonly found in mining. The current methodologies to monitor this type of exposure involve distributed sample collection followed by costly and relatively lengthy follow-up laboratory analysis. To address this concern, we have investigated a data-driven predictive modeling pipeline to predict the amount of silica deposition quickly and accurately on a filter within minutes of sample collection completion. This field-based silica monitoring technique involves the use of small, and easily deployable, Fourier transform infrared (FTIR) spectrometers used for data collection followed by multivariate regression methodologies including Principal Component Analysis (PCA) and Partial Least Squares (PLS). Given the complex nature of respirable dust mixtures, there is an increasing need to account for multiple variables quickly and efficiently during analysis. This analysis consists of several quality control steps including data normalization, PCA and PLS outlier detection, as well as applying correction factors based on the sampler and cassette used for sample collection. While outside the scope of this article to test, these quality control steps will allow for the acceptance of data from many different FTIR instruments and sampling types, thus increasing the overall useability of this method. Additionally, any sample analyzed through the model and validated using a secondary method can be incorporated into the training dataset creating an ever-growing, more robust predictive model. Multivariant predictive modeling has far-reaching implications given its speed, cost, and scalability compared to conventional approaches. This contribution presents the application of PCA and PLS as part of a computational pipeline approach to predict the amount of a deposited mineral of interest using FTIR data. For this specific application, we have developed the model to analyze RCS, although this process can be implemented in the analysis of any IR-active mineral, and this pipeline applied to any FTIR data.

Exposure science is fundamental to the field of occupational safety and health. The measurement of worker exposures to hazardous agents informs effective workplace risk mitigation strategies. The modern era of occupational exposure measurement began with the invention of the personal sampling device, which is still widely used today in the practice of occupational hygiene. Newer direct-reading sensor devices are incorporating recent advances in transducers, nanomaterials, electronics miniaturization, portability, batteries with high-power density, wireless communication, energy-efficient microprocessing, and display technology to usher in a new era in exposure science. Commercial applications of new sensor technologies have led to a variety of health and lifestyle management devices for everyday life. These applications are also being investigated as tools to measure occupational and environmental exposures. As the next-generation placeable, wearable, and implantable sensor technologies move from the research laboratory to the workplace, their role in the future of work will be of increasing importance to employers, workers, and occupational safety and health researchers and practitioners. This commentary discusses some of the benefits and challenges of placeable, wearable, and implantable sensor technologies in the future of work.

In the last years, the issue of exposure assessment of airborne pollutants has been on the rise, both in the environmental and occupational fields. Increasingly severe national and international air quality standards, indoor air guidance values, and exposure limit values have been developed to protect the health of the general population and workers; this issue required a significant and continuous improvement in monitoring technologies to allow the execution of proper exposure assessment studies. One of the most interesting aspects in this field is the development of the "next-generation" of airborne pollutants monitors and sensors (NGMS). The principal aim of this review is to analyze and characterize the state of the art and of NGMS and their practical applications in exposure assessment studies. A systematic review of the literature was performed analyzing outcomes from three different databases (Scopus, PubMed, Isi Web of Knowledge); a total of 67 scientific papers were analyzed. The reviewing process was conducting systematically with the aim to extrapolate information about the specifications, technologies, and applicability of NGMSs in both environmental and occupational exposure assessment. The principal results of this review show that the use of NGMSs is becoming increasingly common in the scientific community for both environmental and occupational exposure assessment. The available studies outlined that NGMSs cannot be used as reference instrumentation in air monitoring for regulatory purposes, but at the same time, they can be easily adapted to more specific applications, improving exposure assessment studies in terms of spatiotemporal resolution, wearability, and adaptability to different types of projects and applications. Nevertheless, improvements needed to further enhance NGMSs performances and allow their wider use in the field of exposure assessment are also discussed.

The mineralogical complexity of mine dust complicates exposure monitoring methods for occupational, respirable hazards. Improved understanding of the variability in respirable dust char-acteristics, e.g., mineral phase occurrence and composition, is required to advance onsite monitoring techniques that can be applied across diverse mining sectors. Principal components analysis (PCA) models were applied separately to XRD and FTIR datasets collected on 130 respirable dust samples from seven mining commodities to explore similarities and differences among the samples. Findings from both PCA models classified limestone, iron, and granite mine samples via their analytical responses. However, the results also cautioned that respirable samples from these commodities may not always fit patterns observed within the model. For example, one unique sample collected in a limestone mine contained no carbonate minerals. Future predictive quantification models should account for unique samples. Differences between gold and copper mine dust samples were difficult to observe. Further investigation suggested that the key to their differentiation by FTIR may lie in the characterization of clays. The results presented in this study provide foundational information for guiding the development of quantification models for respirable mineral hazards in the mining industry.

Field-based methods for the analysis of respirable crystalline silica are now possible with the availability of portable instrumentation. Such methods also require the use of cassettes that facilitate direct-on-filter analysis of field samples. Conventional sampling cassettes can be modified such that they are amenable to direct-on-filter analysis while remaining compatible with common respirable dust samplers. The required modifications are described herein, and one version of such an analysis-ready cassette is described and evaluated in comparison to more traditional cassette designs. The novel cassette was found to result in a slightly higher mass of collected respirable material (for the same sampling duration), though this is likely due to the conductive material of the cassettes, which prevents particle wall losses in comparison to the more commonly used styrene cassette material. Both types of cassettes demonstrated comparable predictability in terms of respirable crystalline silica in a sample.

Background: Small, lightweight, low-cost optical particulate matter (PM) monitors are becoming popular in the field of occupational exposure monitoring, because these devices allow for real-time static measurements to be collected at multiple locations throughout a work site as well as being used as wearables providing personal exposure estimates. Prior to deployment, devices should be evaluated to optimize and quantify measurement accuracy. However, this can turn out to be difficult, as no standardized methods are yet available and different deployments may require different evaluation procedures. To gain insight in the relevance of different variables that may affect the monitor readings, six PM monitors were selected based on current availability and evaluated in the laboratory; (2) Methods: Existing strategies that were judged appropriate for the evaluation of PM monitors were reviewed and seven evaluation variables were selected, namely the type of dust, within- and between-device variations, nature of the power supply, temperature, relative humidity, and exposure pattern (peak and constant). Each variable was tested and analyzed individually and, if found to affect the readings significantly, included in a final correction model specific to each monitor. Finally, the accuracy for each monitor after correction was calculated; (3) Results: The reference materials and exposure patterns were found to be main factors needing correction for most monitors. One PM monitor was found to be sufficiently accurate at concentrations up to 2000 µg/m(3) PM(2.5), with other monitors appropriate at lower concentrations. The average accuracy increased by up to three-fold compared to when the correction model did not include evaluation variables; (4) Conclusions: Laboratory evaluation and readings correction can greatly increase the accuracy of PM monitors and set boundaries for appropriate use. However, this requires identifying the relevant evaluation variables, which are heavily reliant on how the monitors are used in the workplace. This, together with the lack of current consensus on standardized procedures, shows the need for harmonized PM monitor evaluation methods for occupational exposure monitoring.

The exposure of mining workers to crystalline particles, e.g., alpha quartz in respirable dust is a ubiquitous global problem in occupational safety and health at surface and underground operations. The challenge of rapid in-field monitoring for direct assessment and adoption of intervention has not been solved satisfactorily to date, as conventional analytical methods such as X-ray diffraction (XRD) and infrared (IR) spectroscopy require laboratory environments, complex system handling, tedious sample preparation, and are limited by, e.g., addressable particle size. A novel monitoring approach was developed for potential in-field application enabling the quantification of crystalline particles in the respirable regime based on transmission IR spectroscopy. This on-site approach analyzes samples of dust in ambient air collected onto PVC filters using respirable dust sampling devices. In the present study, we demonstrate that portable Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate data analysis provides a versatile tool for the identification and quantification of minerals in complex real-world matrices. Without further sample preparation, the loaded filters are immediately analyzed via transmission IR spectroscopy, and the mineral amount is quantified in real-time using a partial least squares regression (PLSR) algorithm. Due to the inherent molecular selectivity for crystalline as well as organic matrix components, IR spectroscopy uniquely allows to precisely determine the particle composition even in complex samples such as dust from coal mines or clay-rich environments. For establishing a robust PLSR model, a method was developed for generating calibration samples representative in size and composition for respirable mine dust via aerodynamic size separation. Combined with experimental design strategies, this allows tailoring the calibration set to the demands of air quality management in underground mining scenarios, i.e., the respirable particle size regime and the matrix of the target analyte.

Respirable dust can pass beyond ciliated airways of the respiratory tract and influence adverse health effects. Health effects can be studied using samples generated from bulk dust segregation. Because previous segregation methods diverge from size-selection criteria of the international convention for respirable particles (ICRP), a method was developed to approximate the ICRP. The method was compared to an ideal sampler by measuring the sample collection bias. The comparison shows that the uncertainty due to the bias was 0.10 based on European Standard EN13205:2014 criteria, which indicates that the segregator effectively follows the ICRP. Respirable particle size distributions were confirmed by an aerodynamic particle sizer and by computer-controlled scanning electron microscopy. Consequently, a systematic way to generate respirable powders for health effects studies and chemical analyses was developed.

Due to the global need for energy and resources, many workers are involved in underground and surface mining operations where they can be exposed to potentially hazardous crystalline dust particles. Besides commonly known alpha quartz, a variety of other materials may be inhaled when a worker is exposed to airborne dust. To date, the challenge of rapid in-field monitoring, identification, differentiation, and quantification of those particles has not been solved satisfactorily, in part because conventional analytical techniques require laboratory environments, complex method handling, and tedious sample preparation procedures and are in part limited by the effects of particle size. Using a set of the three most abundant minerals in limestone mine dust (i.e., calcite, dolomite, and quartz) and real-world dust samples, we demonstrate that Fourier transform infrared (FTIR) spectroscopy in combination with appropriate multivariate data analysis strategies provides a versatile tool for the identification and quantification of the mineral composition in relative complex matrices. An innovative analytical method with the potential of in-field application for quantifying the relative mass of crystalline particles in mine dust has been developed using transmission and diffuse reflection infrared Fourier transform spectroscopy (DRIFTS) within a unified multivariate model. This proof-of-principle study shows how direct on-site quantification of crystalline particles in ambient air may be accomplished based on a direct-on-filter measurement, after mine dust particles are collected directly onto PVC filters by the worker using body-mounted devices. Without any further sample preparation, these loaded filters may be analyzed via transmission infrared (IR) spectroscopy and/or DRIFTS, and the mineral content is immediately quantified via a partial least squares regression (PLSR) algorithm that enables the combining of the spectral data of both methods into a single robust model. Furthermore, it was also demonstrated that the size regime of dust particles may be classified into groups of hazardous and less hazardous size regimes. Thus, this technique may provide additional essential information for controlling air quality in surface and underground mining operations. Graphical Abstract.

Exposure to dusts containing respirable crystalline silica is a recognized hazard affecting various occupational groups such as miners. Inhalation of respirable crystalline silica can lead to silicosis, which is a potentially fatal lung disease. Currently, miners' exposure to respirable crystalline silica is assessed by collecting filter samples that are sent for laboratory analysis. A more timely field-based silica monitoring method using direct-on-filter (DoF) analysis is being developed by researchers at the National Institute for Occupational Safety and Health (NIOSH) to provide mine operators with the option to evaluate miners' exposure at the mine. This field-based silica monitoring technique involves the use of portable Fourier transform infrared (FTIR) instruments. As a step in the development of this new analytical technique, four commercially available portable FTIR instruments were evaluated for their ability to provide reproducible measurements from filter samples containing respirable crystalline silica. Reported testing indicates that measurements varied within +/-4.1% between instruments for filter samples that contained high-purity respirable crystalline silica. Measurements varied within +/-3.0% between instruments for filter samples that contained varying mineral composition. Filter samples were repeatedly analyzed by the same instrument over short and extended periods of time, and mean coefficients of variation did not exceed +/-1.6 and +/-2.4%, respectively. Mixed model analysis revealed that there was no statistically significant (P < 0.05) change in average measurements made over an extended period of time for all instruments. Results suggest that each of the four FTIR instruments evaluated in this study were able to generate precise and reproducible DoF analysis results of respirable dust samples.

Exposure to respirable crystalline silica (RCS) can cause serious and irreparable negative health effects, including silicosis and lung cancer. Workers in coal mines have the potential of being exposed to RCS found in dust generated by various mining processes. The silica content of respirable dust in one single mine can vary substantially over both time and location. The current monitoring approach for RCS relies on the use of traditional air sampling followed by laboratory analysis. Results generated using this approach are generally not available for several days to several weeks after sampling, and this delay prevents timely and effective intervention if needed. An alternate analytical method is needed to reduce the time required to quantify the RCS exposure of mine workers. The National Institute for Occupational Safety and Health (NIOSH) has developed a new method using commercially available portable infrared spectrometers for measuring RCS at the end of the sampling shift. This paper will describe the application of the new field-based RCS analytical process for coal mines, including the use of the new method with the existing Coal Mine Dust Personal Sampler Unit. In a case study conducted by NIOSH with a coal mine operator in West Virginia, field-based RCS analysis was completed at a mine site to evaluate the new technique. The RCS analysis results obtained by the field-based method in this case study showed sufficiently strong correlation with results obtained by the MSHA standard laboratory analysis method to allow the mine operator to use the field-based method for evaluating process improvements.

To improve worker health protection and support engineering applications in underground mines, such as ventilation-on-demand, capabilities are increasingly sought for continuous monitoring of diesel particulate matter (DPM). For near real-time monitoring over periods up to a full workshift, the FLIR Airtec handheld monitor was developed and calibrated to the NIOSH Standard Method 5040 measure of elemental carbon (EC), which is commonly used as an analytical surrogate for DPM. However, needs still exist for autonomous monitoring over longer periods (e.g., weeks to months). To meet those needs, two commercially available instruments are considered here, the Magee Scientific AE33 Aethalometer and the Sunset Laboratory Semi-continuous OC-EC Field Analyzer. Along with a prototyped monitor called the Airwatch, these were tested head-to-head against the Method 5040 EC and the Airtec in a controlled laboratory setting; and against one another in a field study at an underground mine. Key findings include: the OC-EC field analyzer performed well across a wide range of EC concentrations; the AE33 performed well at relatively low concentrations, but modifications or additional data corrections are likely needed at higher concentrations; and the Airwatch showed good potential, though significant improvements will be required if this instrument is to be further developed, including resolution of several mechanical issues and selection of an appropriate filter material and development of robust data corrections. Moreover, the relative advantages and disadvantages associated with each instrument (e.g., in terms of data quality, complexity and maintenance) must be considered in the context of the intended application and sampling environment.

Video techniques for monitoring exposure, such as NIOSH’s “Helmet-CAM,” employ both real-time dust monitors and mobile video cameras to assess workers’ respirable dust exposures. Many real-time personally worn dust monitors utilize light scattering sensing elements, which are subject to measurement biases as a function of dust type (size, composition, shape factor) and environmental conditions such as relative humidity. These biased and inaccurate dust measurements impair the monitor’s ability to properly represent actual respirable dust concentrations. In the testing described, instrument mass concentration data was collected using three different types of commonly used commercial off-the-shelf personal dust monitors and compared to a reference standard. This testing was performed in a calm air (Marple) dust chamber in which three units of each make and model (for a total of nine monitors) were used for each test. Equivalency factors (EF, a multiplier to match the Thermo TEOM 1400a reference instrument) ranged between 0.746 and 1.879 across all dusts and environmental conditions tested, and between 0.821 and 1.519 on the ISO test dust.

A person-wearable dust monitor that provides nearly real-time, mass-based readings of respirable dust was developed for use in underground coal mines. This personal dust monitor (PDM) combined dust sampling instrumentation with a cap lamp (and battery) into one belt-wearable unit, with the air inlet mounted on the cap lamp. However, obsolescence of belt-carried cap lamp and batteries in coal mining ensued and led end users to request that the cap lamp and battery be removed from the PDM. Removal of these components necessitated the design of a new air inlet to be worn on the miner's lapel. The revised inlet was tested for dust collection equivalency against the original cap-mounted inlet design. Using calculated inlet respirable fractions and measured dust mass collection, the performance of the two inlets is shown to be similar. The new inlet requires a 1.02 factor for converting dust masses obtained from it to equivalent masses collected from the original inlet.

Typcial monitoring procedures for diesel particulate matter (DPM) in mines include the collection of filter samples using particle size selectors. The size selectors are meant to separate the DPM, which is generally considered to occur in the submicron range (i.e., < 0.8 μm), from larger dust particles that could present analytical interferences. However, previous studies have demonstrated that this approach can sometimes result in undersampling, therefore, excluding significant fractions of the DPM mass. The excluded fraction may represent oversized DPM particles, but another possibility is that submicron DPM attaches to supramicron dust particles such that it is effectively oversized. To gain insights into this possibility, a field study was conducted in an underground stone mine. Submicron, respirable, and total airborne particulate filter samples were collected in three locations to determine elemental carbon (EC) and total carbon (TC), which are commonly used as analytical surrogates for DPM. Concurrent with the collection of the filter samples, a low-flow sampler with an electrostatic precipitator was also used to collect airborne particulates onto 400-mesh copper grids for analysis by transmission electron microscope (TEM). Results indicated that, while typical submicron sampling did account for the majority of DPM mass in the study mine, DPM-dust attachment can indeed occur. The effect of exposure to such attached particulates has not been widely investigated.

Diesel particulate matter (DPM) is an occupational health hazard in underground mines. It generally occurs in the submicrometer size range and is often present in the mine atmosphere with significant concentrations of dust particles that tend to occur in the supramicrometer size range. As dust can interfere with analytical methods to measure DPM, it is often removed from a sample stream using an impactor-type size selector such as the DPM impactor (DPMI). Because the DPMI physically removes oversized particles from the stream, its performance may be gradually reduced with aging. Sharp-cut cyclones (SCCs) are an alternative size selector for DPM sampling applications, with a major advantage that, by design, they should not be susceptible to rapid aging. This paper presents the results of a field study designed to compare the performance of aged versus new/clean DPMIs and SCCs in an underground mine. DPMI aging resulted in clogging of the device and, eventually, a reduction of its effective particle cut size, but when sample flow rate was maintained, DPM sample mass collection was not affected until significant aging had occurred. Under the conditions of this study, the effects of SCC aging were observed to be minimal at the end of the study period.

A newly developed high flow rate respirable size-selective cyclone sampler (GK4.162-also known as the Respirable Air Sampling Cyclone Aluminum Large (RASCAL)) was calibrated to determine its optimum operating flow rate. The Health and Safety Laboratory in the United Kingdom and two laboratories from the National Institute for Occupational Safety and Health in the United States conducted experiments using two different methods: (1) polydisperse aerosol and time-of-flight direct reading instrument (Aerodynamic Particle Sizer (APS)) and (2) monodisperse aerosol and APS. The measured performance data for the cyclone was assessed against the international respirable convention using the bias map approach. Although the GK4.162 cyclone was tested using different aerosols and detection methods, the results from the three laboratories were generally similar. The recommended flow rate based on the agreement of results from the laboratories was 9.0 L/min.

Evaluation and control of respirable crystalline silica (RCS) exposures are critical components of an effective mine industrial hygiene program. To provide more timely exposure data in the field, an end-of-shift Fourier transform infrared (FT-IR) spectrometry method has been developed for evaluation of direct-on-filter RCS. The present study aimed to apply this FT-IR method using field samples collected in three Northwestern U.S. metal/nonmetal mines and compare the results to traditional laboratory X-ray diffraction analysis (XRD). Seventy-five dust samples were analysed using both methods. Samples for each mine were split in half by random assignment, with half used to create a calibration factor for the FT-IR analysis and half used to apply the calibration. Non-parametric correlational and two-sample comparative tests were used to assess the strength of association and the level of agreement between the two methods. Strong, positive correlations were observed between FT-IR and XRD RCS concentrations, with Spearman rank correlation coefficients ranging between 0.84 and 0.97. The mean RCS concentrations determined though FT-IR analysis were lower than through XRD analysis, with mean differences ranging from -4 to -133 ug/m(3) and mean percent errors ranging from 12% to 28%. There was a statistically significant improvement in the level of agreement between log FT-IR and log XRD RCS concentrations following calibration at two of the three mines, with mean differences of -0.03 (p = 0.002) and -0.02 (p = 0.044) in the log scale. The reduction in mean difference following calibration at the other mine was not statistically significant (mean log scale difference = -0.05, p = 0.215), but the differences between FT-IR and XRD were not significantly different without calibration (mean log scale difference = -0.07, p = 0.534). The results indicate that mine-specific calibration factors can improve the level of agreement between RCS concentrations determined via a field-based, end-of-shift FT-IR method in metal/non-metal mines as compared to traditional XRD analysis.

Monitoring worker exposure to respirable crystalline silica in dusty environments is an important part of a proactive health and safety program. This is the case for surface copper mines in Arizona and New Mexico. The spatial and temporal variability of respirable dust and crystalline silica concentrations in those mines, coupled with the time lapse in obtaining crystalline silica analysis results from accredited laboratories, present a challenge for an effective exposure monitoring approach and the resulting intervention strategies. The National Institute for Occupational Safety and Health (NIOSH) is developing a novel approach to be used at a mine site for the quantification of crystalline silica in respirable dust samples collected with traditional sampling techniques. The non-destructive analysis is carried out using a portable Fourier transform infrared spectroscopy (FTIR) unit. In this study, respirable dust samples were collected over two visits to each of five copper mines, for a total of ten datasets. The silica in each respirable dust sample was estimated by analyzing the sample with the portable FTIR unit. The quality of the estimation was assessed using the results of the NIOSH 7500 method on the same samples. The confounding effect of other minerals present in the respirable dust in the mines was also assessed, and two quantification approaches were investigated to address it: a sector-specific and a mine-specific approach. The results showed that the sector-specific approach is not effective due to the high variability of relative composition of the minerals among mines. For this approach the combined average relative difference was -13% (-17.6%, -8.9% CI) When using the mine-specific quantification approach, the average relative difference was as low as 2.8% (-3.7%, 9.3% CI); however, this approach was still affected by the variable relative composition of the minerals in the dust in each mine. The use of a multivariate approach on the analysis of each sample was proposed as the next step to achieve consistent low relative differences. This study demonstrates the potential of using a portable FTIR for estimation of crystalline silica in respirable dust samples for in-field exposure monitoring.

The OSHA final rule on respirable crystalline silica (RCS) will require hydraulic fracturing companies to implement engineering controls to limit workers' exposure to RCS. RCS is generated by pneumatic transfer of quartz-containing sand during hydraulic fracturing operations. Chronic inhalation of RCS can lead to serious disease, including silicosis and lung cancer. NIOSH research identified at least seven sources where RCS aerosols were generated at hydraulic fracturing sites. NIOSH researchers developed an engineering control to address one of the largest sources of RCS aerosol generation, RCS escaping from thief hatches on the top of sand movers. The control, the NIOSH Mini-Baghouse Retrofit Assembly (NMBRA), mounts on the thief hatches. Unlike most commercially-available engineering controls, the NMBRA has no moving parts and requires no power source. This article details the results of an evaluation of generation 3 of the NMBRA at a sand mine in Arkansas from May 19 - 21, 2015. During the evaluation, 168 area air samples were collected at 12 locations on and around a sand mover with and without the NMBRA installed. Analytical results for respirable dust and RCS indicated the use of the NMBRA effectively reduced concentrations of both respirable dust and RCS downwind of the thief hatches. Reductions of airborne respirable dust were estimated at 99+%; reductions in airborne RCS ranged from 98-99%. Analysis of bulk samples of the dust showed the likely presence of freshly fractured quartz, a particularly hazardous form of RCS. Use of an improved filter fabric and a larger area of filter cloth led to substantial improvements in filtration and pressures during these trials, as compared to the generation 2 NMBRA. Planned future design enhancements, including a weather cover, will increase the performance and durability of the NMBRA. Future trials are planned to evaluate the long-term operability of the technology.